Research Helps Volunteers Do the Most Good After a Disaster

In the wake of a disaster, many people want to help. Researchers from North Carolina State University and the University of Alabama have developed tools to help emergency response and relief managers coordinate volunteer efforts in order to do the most good.

“Assigning volunteers after a disaster can be difficult, because you don’t know how many volunteers are coming or when they will arrive,” says Maria Mayorga, corresponding author of two studies on the issue and a professor in NC State’s Edward P. Fitts Department of Industrial and Systems Engineering.

“In addition, the challenge can be complicated for efforts, such as food distribution, where you also don’t know the amount of supplies you will have to distribute or how many people will need assistance.”

The researchers used advanced computational models to address these areas of uncertainty in order to develop guidelines, or rules of thumb, that emergency relief managers can use to help volunteers make the biggest difference.

The most recent paper focuses on assigning volunteers to deal with tasks where the amount of work that needs to be done can change over time, such as search and rescue, needs assessment and distribution of relief supplies.

“Essentially, we developed a model that can be used to determine the optimal assignment of volunteers to tasks when you don’t know how much work will be required,” Mayorga says. “For example, in relief distribution, there is uncertainty in both the supply of relief items and what the demand will be from disaster survivors.

“We then used the model to create and test rules of thumb that can be applied even when relief managers don’t have access to computers or the internet.”

The researchers found that a simple policy that performs well is the “Largest Weighted Demand (LWD) policy,” which assigns volunteers to the task that has the most work left to be done. In this case, work is prioritized by its importance. For example, fulfilling demand for water is more important than fulfilling demand for cleaning supplies.

However, if the difference in importance between tasks becomes large enough, then the best option is for managers to assign volunteers based on “Largest Queue Clearing Time (LQCT),” which is the time needed to complete the current work if the current number of volunteers is unchanged.

“In fact, the LQCT heuristic worked well in all of the instances we tested, but it is harder to assess quickly,” Mayorga says. “So we recommend that managers use the LWD rule unless there is a really large difference in the importance of the tasks.”

However, the LWD and LQCT rules of thumb don’t work for all tasks.

In fact, the researchers found that the rules of thumb that make sense for volunteer tasks where you don’t know how much work will be required are actually a bad fit for tasks with clearly defined workloads – such as clearing debris after a disaster.

In a 2017 paper, the researchers found that a good rule of thumb for clearing debris was “Fewest Volunteers,” in which volunteers are simply assigned to whichever task has the fewest volunteers working on it.

“Spontaneous volunteers are people who, in the wake of a disaster, impulsively contribute to response and recovery efforts without affiliations to recognized volunteer organizations (e.g. the Red Cross) or other typical first responders,” Mayorga says. “These people constitute a labor source that is both invaluable and hard to manage.

“Our work in these papers provides strategies for incorporating spontaneous volunteers into organized relief efforts to help us achieve safe and responsive disaster management. It’s also worth noting that these works focused on a single organization assigning volunteers to tasks. In our future work, we are focusing on strategies that can be used by multiple agencies to coordinate efforts and amplify the volunteer response.”

The most recent paper, “Assigning spontaneous volunteers to relief efforts under uncertainty in task demand and volunteer availability,” is published in Omega: the International Journal of Management Science. First author of the paper is Kyle Paret, a Ph.D. student at NC State. The paper was co-authored by Emmett Lodree, an associate professor of operations management at the University of Alabama.

The 2017 paper, “The optimal assignment of spontaneous volunteers,” is published in the Journal of the Operational Research Society. That paper was co-authored by Justin Wolczynski, a former M.S. student at NC State, and by Lodree.

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Note to Editors: The study abstracts follow.

“Assigning spontaneous volunteers to relief efforts under uncertainty in task demand and volunteer availability”

Authors: Kyle E. Paret and Maria E. Mayorga, North Carolina State University; and Emmett J. Lodree, University of Alabama

Published: Feb. 19, 2020, Omega

DOI: 10.1016/j.omega.2020.102228

Abstract: In the wake of a disaster, people from nearby areas often converge to assist the affected community. Spontaneous volunteers are not affiliated with relief agencies but are in a unique position to provide invaluable aid at a crucial point in the disaster cycle. Often, these volunteers are ineffectively used or refused altogether. Volunteer Reception Centers (VRCs) can benefit from improved strategies to integrate the influx of spontaneous volunteers. In this paper, a multi-server queuing model is formulated to represent the dynamics of assigning spontaneous volunteers to tasks in a post-disaster setting. In particular, we consider the case of stochastic arrival of demand for service and stochastic arrival of volunteers, whose time in service is also stochastic. These assumptions mimic disaster relief tasks such as distribution of relief items, where both beneficiaries and volunteers arrive randomly. An optimal policy for assigning volunteers to tasks is generated using a Markov Decision Process. We then use simulation to compare the optimal policy against several heuristic policies and discuss real world implications.

“The optimal assignment of spontaneous volunteers”

Authors: Maria E. Mayorga and Justin Wolczynski, North Carolina State University; and Emmett J. Lodree, University of Alabama

Published: April 5, 2017, Journal of the Operational Research Society

DOI: 10.1057/s41274-017-0219-2

Abstract: Spontaneous volunteers are ordinary citizens who assist in disaster relief efforts, while they are a great resource they also pose a difficult logistical challenge. Unlike classical labor assignment problems, the management of these volunteers is characterized by uncertainty regarding the size, availability, and commitment of the labor pool. We model this problem as a multi-server queueing system with both stochastic server arrival and abandonment. This model is intended to be applied to the relatively stable work associated with recovery efforts, e.g., debris clearing. We model this system as a continuous time Markov decision process and compare the optimal policy to several common-sense heuristics; one of which performs close to optimal and makes a practical alternative. We conduct extensive sensitivity analysis around model parameters and assumptions.